RFmarkerDetector (version 1.0.1)

paretoscale: Pareto scaling method performed on the columns of the data table (i.e. metabolite concentrations measured by 1H NMR or binned 1H NMR spectra)

Description

The function provides a data pretreatment approach called Pareto Scaling. Each column of the table is given a mean of zero by substracting the column column mean from each value in the column; then each value in each column is divided by a scaling factor, represented by the square root of the standard deviation of the column values.

Usage

paretoscale(data, exclude = T)

Arguments

data

a n x p matrix of n observations and p predictors. If the first two columns of the matrix represent respectively the sample names and the class labels associated to each sample, the scaling method should not include these two columns

exclude

a boolean variable. If set to True the scaling method will exclude the first two columns.

Value

a scaled version of the input matrix

Details

This function is useful when variables have significantly different scales. It is generally the preferred option in NMR Metabolomics because it is a good compromise between no scaling (centering) and auto scaling

Examples

#' ## load the included example dataset
data(cachexiaData)
## call paretoscale with the parameter exclude set to TRUE (default) 
## in order to exclude the first two columns of the dataset from scaling
data.scaled <- paretoscale(cachexiaData, exclude = TRUE)